Kidney transplantation has saved many lives since the first successful transplant more than 50 years ago. Although advances in surgical technique and immunosuppressive therapy have resulted in 1-year survival rates greater than 90%. graft dysfunction in the early post-transplant period occurs in up to 30% of transplant recipients. This is an important factor in the ultimate fate of the allograft, as acute rejection in those recipients with delayed graft function results in a 5-year graft survival of only 35%. This observation alone suggests that early diagnosis of acute rejection episodes is imperative if we are to limit nephron loss and maintain allograph function. Magnetic Resonance Imaging (MRI) is well-suited for assessing renal transplant anatomy and function. MRI uses non-nephrotoxic contrast agents and has the spatial resolution to independently assess different anatomical regions. New MR techniques, termed functional MRI, can assess the filtration capacity of glomeruli, regional blood flow within the kidney, and the oxygen bioavailability at the tissue level. To date, no other modality can combine techniques to provide such a comprehensive evaluation of the kidney. If MRI can non-invasively identify the underlying cause of dysfunction, we could potentially avoid biopsy and still target therapy appropriately. The R21 phase of this proposal focuses on optimizing MR perfusion, blood oxygen level dependent (BOLD) MRI, and single kidney filtration rate (skGFR) sequences. Repetitive measurements of MR perfusion, BOLD MRI and skGFR will be performed on adult volunteers in order to determine their reproducibility and natural variability. If successful, this proposal will result in a non-invasive method for evaluating kidney function, which then can be applied to the study of transplanted kidney dysfunction. The R33 phase of this proposal will utilize MR perfusion, BOLD MRI and skGFR in the differentiation of acute rejection from ATN in a population with delayed graft function. In addition to using functional MRI in the diagnosis of transplant dysfunction, we will streamline image analysis to reduce post-processing time and allow widespread clinical application of our techniques.